Context Aware Data Gathering Study

Type 1 Diabetes Clinical Trial

Official title: Development of a Context-aware Glucose Prediction Algorithm in Patients With Type 1 Diabetes

Status Completed

Clinical Trial Summary

Automated Insulin Delivery (AID) systems have now become an important standard-of-care for people with T1D and have demonstrated a reduction, but not elimination, of hypoglycemia during long-term studies. One limitation of current AID systems is that they have no knowledge about the context or environment that a person is currently experiencing. Contextual patterns can potentially improve the performance of an AID by recognizing environments or patterns of living that are related to changes in glucose. The team at OHSU is developing a context-aware glucose prediction algorithm that will capture context data from the patient both indoors and outdoors. This context data will be provided to the algorithm to allow for detecting contextual patterns that might relate to high or low glucose. The goal of this study will be the creation of a data set that will include contextual patterns along with glucose, insulin and physiological data.

Clinical Trial Description

Subjects will be on study for 28 days. Sensor glucose, activity, exercise, insulin, indoor and outdoor contextual patterns and meal data will be collected during this time. Subjects will wear the Dexcom G6 CGM system and a physical activity monitor for the entire 28 days. Subjects will continue to use their own insulin pump. Subjects will be asked to also wear a MotioWear indoor/outdoor context-aware tracking tag and to install the MotioWear beacons within their home. Subjects will be randomized to complete either aerobic, high intensity interval training, or resistance exercise videos twice weekly at home during weeks 1 and 2 and once during weeks 3 and 4. Subjects will also ingest a self-selected meal prior to these prescribed exercise sessions. Subjects will eat a high carbohydrate dinner once each week on the same day at the same approximate time of day (but not on the exercise days). Subjects will use the T1 DEXI mobile app created by OHSU to capture meal and exercise data along with photos of meals the day of exercise and the day after. While at home, subjects will check CBG before and after exercise, for symptoms of hypoglycemia, and for Dexcom G6 alarms for sensor <70 mg/dL and >250 mg/dL. ;

Related Conditions & MeSH terms

• Diabetes Mellitus, Type 1
• Type 1 Diabetes

• NCT number: NCT04154904
• Study type: Interventional
• Source: Oregon Health and Science University
• Status: Completed
• Phase: N/A
• Start date: August 11, 2020
• Completion date: January 3, 2022